Tech jobs: Minorities have degrees, but don"t get hired

Top universities turn out black and Hispanic computer science and computer engineering graduates at twice the rate that leading technology companies hire them, a USA TODAY analysis shows.

Technology companies blame the pool of job applicants for the severe shortage of blacks and Hispanics in Silicon Valley.

But these findings show that claim “does not hold water,” said Darrick Hamilton, professor of economics and urban policy at The New School in New York.

“What do dominant groups say? ‘We tried, we searched but there was nobody qualified.’ If you look at the empirical evidence, that is just not the case,” he said.

As technology becomes a major engine of economic growth in the U.S. economy, tech companies are under growing pressure to diversify their workforces, which are predominantly white, Asian and male. Leaving African Americans and Hispanics out of that growth increases the divide between haves and have-nots. And the technology industry risks losing touch with the diverse nation — and world — that forms its customer base.

On average, just 2% of technology workers at seven Silicon Valley companies that have released staffing numbers are black; 3% are Hispanic.

But last year, 4.5% of all new recipients of bachelor’s degrees in computer science or computer engineering from prestigious research universities were African American, and 6.5% were Hispanic, according to data from the Computing Research Association.

The USA TODAY analysis was based on the association’s annual Taulbee Survey, which includes 179 U.S. and Canadian universities that offer doctorates in computer science and computer engineering.

“They’re reporting 2% and 3%, and we’re looking at graduation numbers (for African Americans and Hispanics) that are maybe twice that,” said Stuart Zweben, professor of computer science and engineering at The Ohio State University in Columbus.

“Why are they not getting more of a share of at least the doctoral-granting institutions?” said Zweben, who co-authored the 2013 Taulbee Survey report.

USA TODAY

An even larger gulf emerges between Silicon Valley and graduates of all U.S. colleges and universities. A survey by the National Center for Education Statistics showed that blacks and Hispanics each made up about 9% of all 2012 computer science graduates.

Nationally, blacks make up 12% of the U.S. workforce and Hispanics 16%.

Facebook, Twitter, Google, Apple and Yahoo declined to comment on the disparity between graduation rates and their hiring rates.

LinkedIn issued a statement that it was working with organizations to “address the need for greater diversity to help LinkedIn and the tech industry as a whole.”

Google said on its diversity blog in May that it has “been working with historically black colleges and universities to elevate coursework and attendance in computer science.”

USA TODAY

In his blog post on diversity, Apple’s CEO Tim Cook cited improving education as “one of the best ways in which Apple can have a meaningful impact on society. We recently pledged $100 million to President Obama’s ConnectED initiative to bring cutting-edge technologies to economically disadvantaged schools.”

All of the companies have insisted they are hiring all of the qualified black and Hispanic tech workers they can find.

In an interview earlier this year, Facebook Chief Operating Officer Sheryl Sandberg said the key to getting more women and minorities into the technology field had to start with improvements to education.

Tech companies lag in hiring minorities

Only half of black and Hispanic graduates with computer science degrees from leading universities are being hired by major technology companies. Percentages of minority staff at seven major companies and minorities graduating with CS degrees from major universities*:

Wage disparity among high-tech workers

Minority tech workers are paid less than their white coworkers, with Hispanic women at the bottom of the pay scale, according to a new study.

“We are not going to fix the numbers for under-representation in technology or any industry until we fix our education system,” she said.

Others say tech giants simply don’t see the programmers right in front of them.

Janice Cuny directs the Computer Education program at the National Science Foundation. She says black and Hispanic computer science graduates are invisible to these companies.

“People used to say that there were no women in major orchestras because women didn’t like classical music. Then in the 1970s they changed the way people auditioned so it was blind, the listeners couldn’t see the players auditioning. Now the numbers are much more representative,” she said.

The same thing happens in the tech world, said Cuny. “There are these subtle biases that make you think that some person is not what you’re looking for, even when they are.”

USA TODAY

One of the key problems: There are elite computer science departments that graduate larger numbers of African-American and Hispanic students, but they are not the ones where leading companies recruit employees. Stanford, UC-Berkeley, Carnegie Mellon, UCLA and MIT are among the most popular for recruiting by tech companies, according to research by Wired magazine.

“That is the major disconnect,” said Juan Gilbert, a professor of computer and information science at the University of Florida in Gainesville.

“The premise that if you want diversity, you have to sacrifice quality, is false,” he said. His department currently has 25 African-American Ph.D. candidates. Rice University in Houston has a large number of Hispanic students.

“These are very strong programs, top-ranked places that have excellent reputations,” he said. “Intel has been hiring from my lab, and they say our students hit it out of the ballpark.”

Justin Edmund says he was fortunate to attend Carnegie Mellon. Today he’s the seventh employee at Pinterest and one of the top designers at the San Francisco start-up valued at $5 billion.

He’s also one of the few African Americans in his company.

“There’s a lot of things that can be done to fix the problem, but a lot of them are things that Silicon Valley and technology companies don’t do,” Edmund said. “If you go to the same prestigious universities every single time and every single year to recruit people … then you are going to get the same people over and over again.”

Contributing: Paul Overberg

via Tech jobs: Minorities have degrees, but don’t get hired.

Tech jobs: Minorities have degrees, but don"t get hired

What"s Driving Greater Adoption of IT Operations Analytics?

With modern business becoming more complex and facing constant changes, unpredictable events, and dynamic demand by the end users – all happening at unprecedented speed – IT Operations & Management is looking to adopt the right tools to optimize operations to handle the complexity and pace of change.

Need to Do More With Less

In 2009, IT budgets fell sharply. According to Gartner, they shrank 8.1 percent in 2009, and another 1.1 percent the year after. Though IT budgets started growing again in 2011, they are only at the level they were in 2005.

At the same time, IT operations teams are running with fewer people and resources, while not only managing an increasing number of systems, but also dealing with the new complexity that comes with hybrid environments and the rapid pace of changes nurtured by agile processes. Increasing productivity while lowering costs seems like a difficult proposition, especially since increased demands are placed on operations staff to manage a variety of rapidly evolving applications across the environment.

Managing Enormous Amounts of Data

Everything from system successes to system failures, and all points in between, are logged and saved as IT operations data. IT services, applications, and technology infrastructure generate data every second of every day. All of that raw, unstructured or polystructured data is needed to manage operations successfully. The problem is that doing more with less requires a level of efficiency that can only come from complete visibility and intelligent control based on the detailed information coming out of IT systems.

Frequent Changes Occur in IT Operations

With the operations staff responsible for the health of the entire business it is in their DNA to resist anything that might introduce unpredictable changes within the IT infrastructure or applications, so much so that IT Ops are rewarded for consistency and for preventing the unexpected or unauthorized from happening.

However, solving business problems requires creativity and flexibility to meet the frequent changes dictated by business requirements. New agile approaches eschew the standard method of releasing software in infrequent, highly tested, comprehensive increments in favor of a near-constant development cycle that produces frequent, relatively minor changes to applications in production. With hundreds or thousands of dependencies, even if the agile iterations are properly tested throughout development, unforeseen problems can arise in production that can seriously affect the stability.

Since every IT service is based on many parameters from different layers, platforms, and infrastructure, a small change in one of the parameters amongst millions of others can create significant impact. When this happens, finding the root cause can take hours and days particularly given the pace and diversity of changes. In many cases unplanned changes lie at the root of many failures. This can create business and IT crises that should be resolved quickly to avoid productivity and business losses.

Traditional Approaches Failed

Problems can be difficult to manage or even identify because so many businesses rely only on monitoring software, which is not sufficient alone to address challenges described above. In fact, problems are often not detected until they have grown out of control. If these issues are not resolved quickly, the result is downtime.

All of the technology infrastructure running an enterprise or organization generates massive streams of data in such an array of unpredictable formats that it can be difficult to leverage using traditional methods or handle in a timely manner. IT operations management based on a collection of limited function and non-integrated tools lacks the agility, automation, and intelligence required to maintain stability in today’s dynamic data centers. Collecting data, filtering it to make it more manageable, and presenting it in a dashboard is nice, but not prescriptive.

One of the holy grails still unresolved in IT management is intelligent IT automation. There are pieces of activities that are automated, targeted at the repetitive, well-known, mundane activities. This can free up people and resources to perform more innovative activities, and offer a more agile, speedy response from IT.

However, while automation is an important tool in the kit, it’s just one of the tools. The effort to automate complex environments is proportional to the complexity. Essentially, automation is just another generation of scripting of those activities that are running as part of operations designed to spawn and manage slave automation gofers.

The Rise of IT Operations Analytics

Given that changes to the operational model are almost guaranteed, a change in perspective is needed where IT operations takes a proactive approach to service management. Applying big data concepts to the reams of data collected by IT operations tools allows IT management software vendors to efficiently address a wide range of operational decisions. Because of the complexity of environments and processes and the dynamics of the environment, organizations need to have automation that is analytics driven.

With all of this data, IT Operations Analytics (ITOA) tools stand as powerful solutions for IT, helping to sift through all of the big data to generate valuable insights and business solutions. IT Operations Analytics can provide the necessary insight buried in piles of complex data, and can help IT operations teams to proactively determine risks, impacts, or the potential for outages that may come out of various events that take place in the environment.

Allowing a new way for operations to proactively manage IT system performance, availability, and security in complex and dynamic environments with less resources and greater speed, ITOA contributes both to the top and bottom line of any organization, cutting operations costs and increasing business value through both greater user experience and reliability of business transactions.

via What’s Driving Greater Adoption of IT Operations Analytics? | Data Center Knowledge.

What"s Driving Greater Adoption of IT Operations Analytics?

Women in Tech You Need to Know

Good news, according to a report released by the Center for American Progress:

The number of women-owned firms in the US grew by 59 percent from 1997 to 2013 — 1.5 times the national average.

Women of color are the majority owners at close to one-third of all women-owned firms in the nation.

African American women are both the fastest-growing segment of the women-owned-business population and the largest share of female business owners among women of color, at 13 percent.

Recently, I asked my folks to contribute names of impressive women in the STEM field who really have their boots on the ground. We got some really good responses, and have compiled an abbreviated list in no particular order. (You can read the full list here.)

1. Bindu Reddy, CEO and Co-Founder of MyLikes

Before starting MyLikes, Bindu was at Google and oversaw product management for several products including Google Docs, Google Sites, Google Video and Blogger. When she first started at Google, Bindu was a Product Manager for AdWords, where she improved the AdWords bidding model by introducing Quality Based Bidding and Quality Score for keywords. She was also in charge of Google’s shopping engine — Google Product Search and designed and launched Google Base.

Before Google, Bindu founded AiYo — a shopping recommendations service. Earlier in her career, Bindu was the Director of Product Management at eLance and a Computational Biologist at Exelixis.

2. Edie Stern, a distinguished Engineer and Inventor at IBM Edie has more than 100 patents to her name, and has been awarded the Kate Gleason Award for lifetime achievement. She received the award for the development of novel applications of new technologies. The 100 patents to her name represent her work in the worlds of telephony and the Internet, remote health monitoring, and digital media.

3. Ellen Spertus, Research Scientist at Google & Computer Science Professor at Mills University

Ellen’s areas of focus are in structured information retrieval, online communities, gender in computer science, and social effects of computing. She was a core engineer of App Inventor for Android, which enables computing novices to create mobile apps. and she co-authored a book on App Inventor.

Ellen has been working to bring more women into computing for decades now. In 1991, while studying computer science at MIT, she published a paper titled, “Why are there so few Female Computer Scientists.” And Ellen tells girls: “I’m sorry to tell you that Hogwarts isn’t real — but MIT is.”

via Women in Tech You Need to Know | Craig Newmark.

Women in Tech You Need to Know 

YouTube offering bonuses to keep talent away from rivals, says WSJ

Google is throwing money at its YouTube stars to keep them away from a site that hasn’t even launched yet, according to the WSJ. Vessel, created by Hulu exec Jason Kilar, has offered some YouTube artists exclusive and lucrative deals to attract attention to its launch later this year. Other sites like Facebook and Crackle have also reportedly been poaching YouTube stars. The “broadcast yourself” site leans on talent like style coach Michelle Phan and comedian Colleen Ballinger (as Miranda Sings, above) to keep loyal channels fans engaged. But Phan, who had an early look at Vessel, called it “stunning,” and others have said that they were offered serious money for exclusive deals. Artists that stay loyal are making out better, though — on top of bonuses, YouTube has been offering rich funding deals to help select stars create new channels.

via YouTube offering bonuses to keep talent away from rivals, says WSJ.

YouTube offering bonuses to keep talent away from rivals, says WSJ

How To Hire Like Google And Facebook: Evaluating Candidates Beyond Their Technical Ability

In a previous Forbes post, we considered the disconcerting reality that even in the midst of an unemployment crisis, employers across industries are still unable to find the talent profiles they need. How is it possible that even highly educated candidates are unable to find skilled work when millions of open positions go unfilled? Evidence indicates that this talent gap is not due to the absence of technical skills, as one might expect, but rather to the absence of “soft skills,” or what we’ll call 21st century skills, in prospective candidates. These primarily refer to interpersonal and general analytic abilities like teamwork, empathy, leadership, negotiation, adaptability, and problem solving.

As we discussed, this is useful information for students and educators, but lessons from this research could be of particular benefit to employers, as well. The problem is that 21^st century skills are very difficult to assess with any kind of rigor, especially before one can evaluate a candidate on the job. Can a candidate think innovatively? Collaborate with other team members? Assimilate feedback and coaching? Will the candidate be adaptable to new environments and successfully integrate with teams? It is very difficult to reduce these questions to discrete qualifications and quantifiable metrics in the same way we assess recognized degrees and numerical grades.

Certainly some approaches exist. For example, businesses have used “type”-based personality tests for decades in attempts to measure the soft skills of prospective candidates, assuming that certain personality types would correlate with high performance. One example is the Jung Typology Profiler for Workplace™ (JPTW), which purports to measure qualities such as “Power” (leadership potential), “Assurance,” “Visionary,” “Rationality,” and so forth.

Despite the promise of measuring key skills, the reality is that personality tests have serious methodological flaws and lack the statistical reliability to predict performance among prospective employees. For example, the Myers-Briggs Type Indicator (MBTI) is a closely-related profiler to the JPTW that also has its origins in Jungian typology from the early 20th century. The makers of the MBTI clearly state in their ethical guidelines that “It is unethical, and in many cases illegal, to require job applicants to take the Indicator if the results will be used to screen out applicants.” Because of their shared methodological limitations, the same restrictions should apply to the JPTW.

It’s clear that we need 21^st century methods to assess 21^st century skills. Unfortunately, that seemingly simple idea proves to be much trickier in practice than it is in theory.

Tools for talent development do not work for pre-employment screening

Part of the problem is that many companies are using the wrong tools for the job.   There is a fundamental difference between tools intended to develop existing teams and tools used for pre-employment selection.

For developing existing teams, there is evidence that “type”-based  personality tests can help managers better develop and deploy the talent they have already hired. For example, Gallup’s StrengthsFinder 2.0 is a tool that helps individuals understand and describe their own talents, and is commonly used by managers to understand and capitalize on the strengths of those they hire. More importantly, it is methodologically sound, and its reliability and validity are backed up by clear evidence.

For example, Facebook uses StrengthsFinder in a clever way to deploy talent efficiently. Regardless of the job openings they have available, Facebook simply hires the smartest people it can find, then uses StrengthsFinder results to understand their talents and create a job tailored to the candidate.

One might naturally assume that the same type of test that helps identify and develop strengths in an existing team could also be used to assess suitable candidates for entry into that team. In the words of Gallup, “Absolutely not… A development-oriented assessment such as StrengthsFinder is markedly different from selection tools because its purpose is not to assess whether an individual is suited for a particular job or role. Instead, it aims to provide talent insights for developing strengths within roles.”

Personality tests cannot be used for the same purpose as pre-employment selection tools because they simply can’t perform the key function: predicting employee performance. For example, two people who have the same set of innate strengths (according to a personality test) could have widely varying job performance. And of course, two people with a completely different set of strengths could do the same job equally well.

Pre-employment selection tools can predict employee performance on the job

Many pre-employment selection tools succeed at predicting performance because they have a completely different design than talent development tools like personality tests. Instead of seeking general traits and preferences, selection tools are tailored to a particular job in a particular organization, and are statistically calibrated to provide reliable predictive results (i.e., candidates who score highly on these tests also tend to perform well after they’re hired). In addition to the StrengthsFinder development tool, Gallup also offers these pre-employment selection tools, which include analytic services to confirm the validity and predictive value of the measures for candidate screening.

Pairin, Inc. is another organization that seeks to combine the personality test approach with specialized testing (for specific jobs, values, culture, etc.) as part of a pre-employment selection system. Using the Job Pairin System, employers can assess the presence of around 100 coachable/changeable behaviors such as emotional intelligence, leadership, attraction of followers, and even character.

A new spin on the behavioral interview

While services from Gallup and Pairin provide strong, evidence-based methods, the debate on using metrics to assess 21^st century skills will certainly continue. For good or bad, it is unlikely that the traditional way to measure 21^st century skills – the behavioral interview – will be unseated anytime soon. (Behavioral interviews are those that include situational questions like “Tell me about a time when you worked effectively under pressure.”)

Certainly, behavioral interviewing has problems of its own – for example, canned and otherwise disingenuous responses are all too common. While most companies still use a behavioral interviewing approach, those with top hiring practices are able to mitigate these issues. First and most importantly: skilled interviewers are often able to weed out rote responses by probing on the details of the situation discussed. This can help get the candidate “off script” and thus generate better insights about their true personality.

The behavioral questions themselves can also be written in a way that yields better insights. For example, Teach for America includes tough questions like “What would cause you to want to dropout of Teach For America if you were chosen?” Questions like these, for which the “obvious” answers might not be the best, could evoke a wider spread between canned responses and those that show more nuance and self-awareness.

As another example of innovation, Google also uses behavioral interviews, but structures them in a way that allows HR to perform analytics and prove that certain responses reliably predict employee performance.

Beyond the interview

Whatever method companies use to assess 21^st century skills in prospective employees, it’s important that they reflect on the key principles behind the assessment approaches. Findings from research on 21^st century skills provide an extremely valuable lens through which companies can view all interactions with candidates. Consider: What can you teach a new hire on the job, and what can you not teach? With information now abundantly available to us, almost anyone can learn basic Photoshop skills, for example, via online seminars. But what about skills like adaptability and empathy – can they be taught on the job?

via How To Hire Like Google And Facebook: Evaluating Candidates Beyond Their Technical Ability – Forbes.

How To Hire Like Google And Facebook: Evaluating Candidates Beyond Their Technical Ability

Data-Driven Marketing Holds the Key to Sales Says Linkedin Exec Russell Glass

The rising importance of data to companies (organizations in general and marketing departments in particular) is changing the perception of marketing’s value. In fact, marketing is now so important that CMOs will make the best next-generation CEOs—thanks to their understanding of data and the customer.

Meet Dan Siroker, a new kind of marketer.

As the Obama campaign’s director of analytics in 2008, one of Siroker’s key responsibilities was optimizing the campaign’s website, a critical fundraising tool. Using sophisticated A/B testing, which involved comparing the results of 24 combinations of visuals, copy and calls-to-action, Siroker and his team identified the most effective combination for raising campaign funds from Obama supporters. Not only did this winning combination raise an extra $60 million for the campaign, as Siroker explained in this blog post, but the A/B testing also generated the data to prove it.

Marketing teams have historically found it hard to be considered a revenue center vs. a cost center. But when you generate $60 million—and show exactly how you did it—there’s no longer any doubt.

Now the CEO and co-founder of Optimizely, Siroker is just one of many pioneering, data-driven marketing executives who have become CEOs. Former marketing executive Paul Pellman was the CEO of Adometry before it was bought by Google earlier this year. Audi, Royal Dutch Shell, and Gilt Groupe have all recently named former marketing executives to CEO roles.

Here’s why this is a big deal

Only the marketing department has a clear window on the behavior of the prospect during 90 percent of the buyer’s decision making—the time spent doing research via visits to websites, reading online reviews, connecting with peers on social media and conducting online searches.

With the data created by this online behavior, marketers possess tremendous insight into their companies’ potential customers. “When I tell people that we can know, in real time, every single visitor when they arrive on our site and know what company type they are from and that we can target specific titles or regions or individual companies, they’re blown away,” says Bill Macaitis, former CMO of Zendesk, describing the company’s ability to understand their prospects in real time.

Marketing now holds the key to sales commissions

Marketing’s possession of this insight into the customer represents a huge shift from the past when the sales department played a much larger role in shepherding the prospect through the sales process. But now, the sales department has little direct knowledge of 90 percent of the buyer’s journey. It is now the marketing department, using data gleaned from the digital footprints left by prospects, that has the insight into this major portion of the sales process. And marketing can supply salespeople with exactly what they need: the qualified leads that are their lifeblood.

So data brings marketing and sales together. And because data can also identify deals that were marketing-sourced, the finance team also gains a new respect for marketing and its contribution to revenue. And finally, these changes have brought marketing closer together with the IT department, which helps install the marketing automation software, analytics tools and dashboards it needs to read the digital body language of customers and prospects.

Marketing is now at the nexus of business

The CMO’s team has the clearest window into customer and prospect behavior. To sales, the CMO delivers the leads most likely to buy to sales. To finance, the CMO shows his or her team’s revenue contribution. And with IT, the CMO helps built out the marketing technology stack that mediates critical interactions with customers and prospects.

The winning companies of the future will be data-driven and customer-focused. No one is in a better position to lead this kind of company than the CMO—the executive who is eminently qualified to be your next CEO.

via Data-Driven Marketing Holds the Key to Sales Says Linkedin Exec Russell Glass | Adweek.

Data-Driven Marketing Holds the Key to Sales Says Linkedin Exec Russell Glass

Don"t Rely On Salary Data To Pick A Programming Language To Learn

You can get paid a lot of money to code COBOL, but that’s probably a career-limiting choice. The less popular a language, the more an employer will be likely to pay. It’s a simple matter of supply and demand—or, as MongoDB’s Kelly Stirman defines it, “revenue potential and adoption [are] inversely proportional.”

Which is why Quartz’s list of the “most valuable programming skills to have on a resume” is wrong-headed and deceiving. Which programming language is “best” depends on a host of factors, perhaps the least important of which is how much that skill will pay you today.

Popularity Contests

After all, the best programming language may well be the one that is most likely to help you consistently find a job, not necessarily the one that pays best.

By that metric, Redmonk’s quarterly list of popular programming languages (culled from matching data from GitHub and Stack Overflow) may be a better place to start when figuring out which language to learn next:

Source: Redmonk

In this ranking, Java and JavaScript remain neck-and-neck for the top spot, with Google’s Go language rocketing up the charts to #21. So is one more important than the other?

Maybe.

As Pivotal’s chief scientist Milind Bhandarkar stresses:

Bhandarkar is correct, but while there may not be an objective way to evaluate the importance of programming languages across the industry, there is absolutely a subjective way for each developer to determine the best language for her. Namely, pick the language that matches where you see the future going.

Defining The Future

So, for example, cloud expert Simon Wardley notes, “If the Internet is the operating system then JavaScript is its language.”

And if you believe cloud is the future, well, Go should be high on your list, as it’s the “most interesting [language] in the cloud era” because it “solve[s] hard problems easily,” according to Red Hat’s Paul Lundin.

Mobile? Hard to argue against learning Swift (Apple) or Java (Android).

And if you don’t trust your own judgment, programming language popularity rankings like the one Redmonk assembles can provide a cheat sheet on the future. Just watch for big spikes in popularity like we’ve seen with Go.

Or look for relative popularity with employers, not ranked by salary but instead by volume of jobs. By that metric Ruby is waning, Python is relatively constant and Go is exploding, according to Indeed.com data. But if you really want to see hyper-growth, Node.js may best them all:

Source: Indeed.com

The Web, presumed dead, seems to be doing quite well.

Getting Paid To Code What You Love

Not that developers must always choose between future relevance and present salary. Quartz’s list sports a number of languages that both pay well and are popular, like JavaScript and Python (an excellent all-around language that doubles as a Big Data heavyweight):

Source: Quartz

Indeed, it’s unlikely that learning any programming language could be considered a bad investment these days, what with developers becoming market makers. Enterprises are falling all over themselves to hire and motivate developers, a trend that won’t diminish anytime soon.

With this in mind, do what you love. And code in the language that best expresses the future you most want to see. There’s never been a better time to be a developers, whatever the programming language you choose.

via Don’t Rely On Salary Data To Pick A Programming Language To Learn – ReadWrite.

Don"t Rely On Salary Data To Pick A Programming Language To Learn